Fall 2022

Quantifying Uncertainty: Stochastic, Adversarial, and Beyond

Sep 12, 2022 to Sep 16, 2022 

Add to Calendar


Thodoris Lykouris (MIT; chair), Laura Doval (Columbia University), Kevin Jamieson (University of Washington)

The workshop will explore online decision-making under different modeling assumptions on the reward structure. The two classical approaches for that consist of the setting where rewards are stochastic from a distribution and the one where they are adversarially selected. We will discuss different hybrid models to go between these extremes (data-dependent algorithms that adapt to “easy data”, model-predictive methods, ML-augmented algorithms, etc). We will also consider settings where the rewards come from agents with particular behavioral or choice models and how the algorithms need to change to adapt to that.

Registration is required to attend this workshop. Space may be limited, and you are advised to register early. The link to the registration form will appear on this page approximately 10 weeks before the workshop. To submit your name for consideration, please register and await confirmation of your acceptance before booking your travel.

Further details about this workshop will be posted in due course. To contact the organizers about this workshop, please complete this form.

Please note: the Simons Institute regularly captures photos and video of activity around the Institute for use in videos, publications, and promotional materials.